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Institute of Medicine (US) Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington (DC): National Academies Press (US); 2001.

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Crossing the Quality Chasm: A New Health System for the 21st Century.

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5Building Organizational Supports for Change

Between front-line clinical care teams and the health care environment lies an array of health care organizations, including hospitals, managed care organizations, medical groups, multispeciality clinics, integrated delivery systems, and others. Leaders of today's health care organizations face a daunting challenge in redesigning the organization and delivery of care to meet the aims set forth in this report. They face pressures from employees and medical staff, as well as from the local community, including residents, business and service organizations, regulators, and other agencies. It is difficult enough to balance the needs of those many constituencies under ordinary circumstances. It is especially difficult when one is trying to change routine processes and procedures to alter how people conduct their everyday work, individually and collectively.

This chapter describes a general process of organizational development and then offers a set of tools and techniques, drawing heavily from engineering concepts, as a starting point for identifying how organizations might redesign care. Chapter 3 offered a set of rules that would redesign the nature of interactions between a clinician and a patient to improve the quality of care. This chapter describes how organizations can redesign care to systematically improve the quality of care for patients. This is not an exhaustive list of possible approaches, but a sampling of techniques used in other fields that might have applicability in health care. The broad areas discussed in this chapter apply to all health care organizations; the specific tools and techniques used would need to be adapted to an organization's local environment and patients.

Recommendation 7: The Agency for Healthcare Research and Quality and private foundations should convene a series of workshops involving representatives from health care and other industries and the research community to identify, adapt, and implement state-of-the-art approaches to addressing the following challenges:

  • Redesign of care processes based on best practices
  • Use of information technologies to improve access to clinical information and support clinical decision making
  • Knowledge and skills management
  • Development of effective teams
  • Coordination of care across patient conditions, services, and settings over time
  • Incorporation of performance and outcome measurements for improvement and accountability

To achieve the six aims identified in Chapter 2, board members, chief executive officers, chief information officers, chief financial officers, and clinical managers of all types of health care organizations will need to take steps to redesign care processes. The recommended series of workshops is intended to serve multiple purposes: (1) to help communicate the recommendations and findings of this report and engage leaders and managers of health care organizations in the pursuit of the aims, (2) to provide knowledge and tools that will be helpful to these individuals, and (3) to encourage the development of formal and informal networks of individuals involved in innovation and improvement.

STAGES OF ORGANIZATIONAL DEVELOPMENT

The design of health care organizations can be conceptualized as progressing through three stages of development to a final stage that embodies the committee's vision for the 21st-century health care system, as represented by the six aims set forth in Chapter 2 (see Table 5–1). Although settings and practices vary, the committee believes much of the health sector has been working at Stages 2 and 3 over the last decade or more. As knowledge and technologies continue to advance and the complexity of care delivery grows, the evolution to Stage 4 will require that Stage 3 organizations accelerate efforts to redesign their approaches to interacting with patients, organizing services, providing training, and utilizing the health care workforce.

TABLE 5–1. Stages of Evolution of the Design of Health Organizations.

TABLE 5–1

Stages of Evolution of the Design of Health Organizations.

Stage 1

Stage 1 is characterized by a highly fragmented delivery system, with physicians, hospitals, and other health care organizations functioning autonomously. The scope of practice for many physicians is very broad. Patients rely on physician training, experience, and good intentions for guidance. Individual clinicians do their best to stay abreast of the literature and rely on their own practice experience to make the best decisions for their patients. Journals, conferences, and informal consultation with peers are the usual means of staying current. Information technology tools are almost entirely absent. Norman (1988) has characterized this approach to work as based on “knowledge in the head,” with heavy dependence on learning and memory. The patient's role tends to be passive, with care being organized for the benefit of the professional and/or institution.

Stage 2

Stage 2 is characterized by the formation of well-defined referral networks, greater use of informal mechanisms to increase patient involvement in clinical decision making, and the formation of loosely structured multidisciplinary teams. For the most part, health care is organized around areas of physician specialization and institutional settings. Patients have more access to health information through print, video, and Internet-based materials than in Stage 1, and more formal mechanisms exist for patient input. However, these tend to be generic mechanisms, such as consent forms and satisfaction surveys. Patients have informal mechanisms for input on their care.

Most health data are paper based. Little patient information is shared among settings or practices; the result is often gaps, redundancy of data gathering, and a lack of relevant information. In this stage, institutions and specialty groups, for example, try to help practitioners apply science to practice by developing tools for knowledge management, such as practice guidelines.

Stage 3

In Stage 3, care is still organized in a way that is oriented to the interests of professionals and institutions, but there is some movement toward a patient-centered system and recognition that individual patients differ in their preferences and needs. Team practice is common, but changes in roles are often slowed or stymied by institutional, labor, and financial structures, as well as by law and custom. Some training for team practice occurs, but that training is typically fragmented and isolated by health discipline, such as medicine, nursing, or physical therapy.

Clinicians and managers recognize the increasing complexity of health care and the opportunities presented by information technology. Some real-time decision support tools are available, but information technology capability is modest, and stand-alone applications are the rule. Computer-based applications for laboratory data, ordering of medications, and records of patient encounters typically cannot exchange data at all or are not based on common definitions. Practice groups—particularly those that are community based—typically lack information systems to make such decision support tools available at the point of patient care, or to integrate guidelines with information about specific patients. Clinical leaders recognize the need for what has been called “knowledge in the world” (Norman, 1988)—information that is retrievable when needed, replaces the need for detailed memory recall, and is continuously updated on the basis of new information. More organized groups rely on best practices, guidelines, and disease management pathways for clinicians and patients, but these are not integrated with workflow.

Stage 4

Stage 4 is the health care system of the 21st century envisioned by the committee. This system supports continued improvement in the six aims of safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity. Health care organizations in this stage have the characteristics of other high-performing organizations. They draw on the experiences of other sectors and adapt tools to the unique characteristics of the health care field.

Patients have the opportunity to exercise as much or as little control over treatment decisions as they choose (as long as their preferences fall within the boundaries of evidence-based practice). Services are coordinated across practices, settings, and patient conditions over time using increasingly sophisticated information systems.

Whatever their form, health care organizations can be characterized as “learning organizations” (Senge, 1990) that explicitly measure their performance along a variety of dimensions, including outcomes of care, and use that information to change or redesign and continually improve their work using advanced engineering principles. They make efficient and flexible use of the health workforce to implement change, matching and enhancing skill levels to enable less expensive professionals and patients to do progressively more sophisticated tasks (Christensen et al., 2000).

The committee does not advocate any particular organizational forms for the 21st-century health care system. The forms that emerge might comprise corporate management and ownership structures, strategic alliances, and other contractual arrangements (“virtual” organizations) (COR Healthcare Resources, 2000; Robinson and Casalino, 1996; Shortell et al., 2000a). New information and delivery structures might be located in a particular city or region or might be the basis for collaborative networks or consortia (COR Health LLC, 2000). Whatever the organizational arrangement, it should promote innovation and quality improvement. Every organization should be held accountable to its patients, the populations it serves, and the public for its clinical and financial performance.

In some respects, such as economies of scale, workforce training and deployment, and access to capital, larger organizations will have a comparative advantage. In other cases, small systems will evolve to take on functions now performed by larger organizations. The use of intranet- or Internet-based applications and information systems may enable the development of an infrastructure to accomplish certain functions. New forms might include, for example, Web-based knowledge servers or broker-mediated, consumer-directed health care purchasing programs.

KEY CHALLENGES FOR THE REDESIGN OF HEALTH CARE ORGANIZATIONS

Health care services need to be organized and financed in ways that make sense to patients and clinicians and that foster coordination of care and collaborative work. They should be based on sound design principles and make use of information technologies that can integrate data for multiple uses (Kibbe and Bard, 1997a; Rosenstein, 1997). Whatever their form, organizations will need to meet six challenges, see Figure 5–1, that cut across different health conditions, types of care (such as preventive, acute, or chronic), and care settings:

FIGURE 5–1. Making change possible.

FIGURE 5–1

Making change possible.

  • redesigning care processes;
  • making effective use of information technologies;
  • managing clinical knowledge and skills;
  • developing effective teams;
  • coordinating care across patient conditions, services, and settings over time; and
  • incorporating performance and outcome measurements for improvement and accountability.

The following discussion of these six challenges includes excerpts from interviews with clinical leaders conducted as a part of an IOM study aimed at identifying exemplary practices (Donaldson and Mohr, 2000).

Redesigning Care Processes

I try to help people understand that we can “work smarter.” You can feel rotten about how you are practicing. I tell them, “You are right—and it's going to get worse.” But change is possible. We don't need a billion-dollar solution.

We need a billion $1 solutions. You have to create the will to change. There's the will to change, then execution.—Hospital-based endoscopy unit

Like any complex system, health care organizations require sophisticated tools and building blocks that allow them to function with purpose, direction, and high reliability. Effective and reliable care processes—whether registering patients who come to the emergency room, ensuring complete immunizations for children, managing medication administration, ensuring that accurate laboratory tests are completed and returned to the requesting clinician, or ensuring that discharge from hospital to home after a disabling injury is safe and well coordinated—can be created only by using well-understood engineering principles. Not only must care processes be reliable, but they must also be focused on creating a relationship with a caregiver that meets the expectations of both the patient and the family. Redesign can transform the use of capital and human resources to achieve these ends.

Redesign may well challenge existing practices, data structures, roles, and management practices, and it results in continuing change. It involves conceptualizing, mapping, testing, refining, and continuing to improve the many processes of health care. Redesign aimed at increasing an organization's agility in responding to changing demand may be accomplished through a variety of approaches, such as simplifying, standardizing, reducing waste, and implementing methods of continuous flow (Bennis and Mische, 1995; Goldsmith, 1998).

Students of organizational theory have learned a great deal through careful examination of the work of organizations that use very complex and often hazardous technologies. The committee's earlier report, To Err Is Human, outlines the achievements of several manufacturing companies and the U.S. Navy's aircraft carriers in using replicable strategies to achieve great consistency and reliability (Institute of Medicine, 2000). Other world-class businesses, notably those that have received the prestigious Malcolm Baldrige National Quality Award, have embraced many of the tenets of quality improvement described by Deming, Juran, and others (Anderson et al., 1994), which include the need to improve constantly the system of production and services. Yet few health care organizations have developed successful models of production that reliably deliver basic effective services, much less today's increasingly advanced and complex technologies. Nor have most been able to continually assess and meet changing patient requirements and expectations.

Some health care organizations have dedicated considerable energy and resources to changing the way they deliver care. Although these organizations have recognized the need for leadership to provide the necessary commitment to and investment in change, they have also recognized that change needs to come from the bottom up as front-line health care teams recognize opportunities for redesigning care processes and acquire the skill to implement those new approaches successfully (National Committee for Quality Health Care, 1999; Washington Business Group on Health, 1998). Many other organizations have taken steps toward redesigning processes, but have found replication and deployment difficult or short-lived (Blumenthal and Kilo, 1998; Shortell et al., 1998). The committee recognizes these efforts and the difficulties that stem from, among other things, restructuring and economic pressure, misaligned incentives, professional entrenchment, competing priorities, organizational inertia, and lack of adequate information systems (Shortell et al., 1998).

A growing body of literature in health care indicates that well-designed care processes result in better quality (Desai et al., 1997; Griffin and Kinmouth, 1998). Some have argued that health care is not amenable to quality improvement approaches derived from other industries because inputs (patients) are so variable; outputs, such as health-related outcomes, so ill-defined; and the need for expert judgment and improvisation so demanding. Similar arguments have been made, but not substantiated, in other service industries and by those in the specialized departments (e.g., legal) of manufacturing industries that have subsequently experienced success in embracing principles of quality improvement (Galvin, 1998). Fortunately, useful redesign principles that are now used widely in other industries can be (and in some cases have been) adapted to health care.

Engineering principles have been widely applied by other industries and in some health care organizations to design processes that improve quality and safety (Collins and Porras, 1997; Donaldson and Mohr, 2000; Hodgetts, 1998; Kegan, 1994; Peters and Waterman, 1982). The following subsections describe five such principles and their use by health care professionals to improve patients' experiences and safety, the flow of care processes, and coordination and communication among health professionals and with patients (Langley et al., 1996).

System Design Using the 80/20 Principle

The nurse assesses the patient demographics, risk factors, support available, medication, lifestyle, and barriers to making changes. The first visit is usually 45 minutes to an hour long. Preventive screening visits are done yearly—assess vital signs, behavior, willingness to make changes. We take retinal photos, which are sent directly to the ophthalmologist, instead of sending the patient there. We learned that we need to risk stratify and fit the level of services to the level of risk. Services are less or more intense based on risk. We use protocols to identify risk level: primary—those with diabetes, secondary—those with diabetes and any other risk factors, tertiary—those who have already had a stroke, myocardial infarction, or renal failure.—Diabetic management group

This engineering principle can be restated: Design for the usual, but recognize and plan for the unusual. Process design should be explicit for the usual case—for 80 percent of the work. For the remaining 20 percent, contingency plans should be assembled as needed. This concept is useful both for designing systems of care and as an approach to acculturating new trainees. Also referred to as the Pareto Principle, the 80/20 principle is based on the recognition that a small number of causes (20 percent) is responsible for a large percentage (80 percent) of an effect (Juran, 1989; Transit Cooperative Research Program, 1995). In health care, for example, 20 percent of patients in a defined population may account for 80 percent of the work and incur 80 percent of costs. Similarly, 20 percent (or fewer) of common diagnoses may account for 80 percent of patients' health problems.

A fundamental approach in health care has been to build care systems to accommodate all possible occurrences. This approach is cumbersome and often the source of delays when, for example, laboratory tests are done in case a rare disease is present, or certain procedures must be followed in case an unusual event should happen. System design based on the 80/20 approach exploits the existence of routine work, often a large proportion of the total work load, that is involved in an assortment of patient problems. One determines what work is routine and designs a simple, standard, and low-cost process for performing this work efficiently and reliably. This leaves the more complex work to be performed employing processes that appropriately use higher-skilled personnel or more advanced technologies.

In accordance with this principle, approaches to planning care are designed to reflect the different sorts of clinical problems encountered in practice. Level 1 represents the most predictable needs. In a pediatric practice, well-child health supervision, immunization, and middle-ear infections represent a large portion of the work and very predictable needs. In an obstetrics-gynecology practice, prenatal care and contraceptive counseling are examples of Level 1. In adult primary care, examples include management of hypertension, acute sprains, low back pain, and sinusitis. For newly diagnosed patients with asthma, instruction in the use of an inhaler is an example of predictable work. The more predictable the work, the more it makes sense to standardize care so that it can be performed by a variety of workers in a consistent fashion.

When needs are predictable, standardization encompasses the key dimensions of work that should be performed the same way each time using a defined process and is a key element of the principle of mass customization discussed later in this section. For example, variation in the care of patients with community-acquired pneumonia can be reduced by identifying and standardizing the key dimensions of care. Standardization may involve very complex or very simple technologies and processes. An example of the latter is a nursing assistant stamping on a patient's chart, “Immunization up to date?” and circling “Yes” or “No” for a clinician to see as he or she enters the exam room. Focused standardization often entails simplifying processes. For example, instead of each clinician on staff having a different protocol, clinicians might agree to use a single chemotherapy protocol for most patients, or a single dose, route, or frequency for a commonly administered medication. Although it might be permissible to use other protocols, clinicians would have to agree to evaluate the outcomes for patients under both the standard and nonstandard protocols to determine which was best (Institute of Medicine, 2000). In another example, Duke University's pediatric emergency department uses a color-coded tape to measure a child's length and an approximate weight range. Color-coded supplies (e.g., IV tubing, airway masks, syringes) correspond to the four weight ranges. Standardizing equipment for each color zone ensures that dosages and equipment are appropriate and safe for children in that range (Glymph, 2000).

Level 2 represents health care needs of medium predictability. At this level, it is important for practice settings to triage patients accurately to determine their needs. Examples are patients with chronic illnesses, such as asthma or diabetes, whose condition is not under control and who need special services to help them. Some patients might best be served by group visits with a diabetic counselor, others might need individual support, and others might need hospitalization. Appropriate triage based on needs could include working out a care plan with patients in terms of exercise, weight loss, and insulin control and providing them with materials and resources to help them meet their objectives.

Level 3 represents patients with rare or complex health care health conditions for which special resources must be assembled. In such cases, applying excellent listening skills, assembling resources, and managing the clinician-patient relationship are especially important. Examples are a patient with an infectious disease that is rare and difficult to identify, or the need to assemble a multidisciplinary team for health supervision of children with special needs, such as those with cystic fibrosis, meningomyelocele, or craniofacial syndromes (Carey, 1992).

The assembling of these resources can sometimes be accomplished within a single office practice. In other cases, a relationship with another system—another critical care unit or an individual such as a subspecialist, for example—may be required. Recent evidence indicates that for ambulatory care, nurses and nurse practitioners can manage a substantial proportion of the work (Mundinger et al., 2000; Shum et al., 2000). The remaining 20 percent of the work would correspond to the third level, which requires the most highly trained practitioners.

Design for Safety

When lab results are returned by e-mail, they come back by provider, and I can attach them to the patient's chart. When I open the patient record, the “desktop” flags alert me to abnormal results.—Primary care practice

The doctor-patient relationship is important, but perhaps more important is how much [doctors] can rely on the system not to let [the patient] slip through the cracks.—Primary care practice

The prevention, detection, and mitigation of harm occur in learning environments, not in environments of blame and reprisal. Designing systems for safety requires specific, clear, and consistent efforts to develop a work culture that encourages reporting of errors and hazardous conditions, as well as communication among staff about safety concerns. Such learning also requires attention to effective knowledge transfer, including the systematic acquisition, dissemination, and incorporation of ideas, methods, and evidence that may have been developed elsewhere (Institute of Medicine, 2000). As described in detail in the committee's earlier report, To Err Is Human (Institute of Medicine, 2000), designing health care processes for safety involves a three-part strategy: (1) designing systems to prevent errors, (2) designing procedures to make errors visible when they do occur, and (3) designing procedures that can mitigate the harm to patients from errors that are not detected or intercepted (Nolan, 2000).

Designing systems to prevent errors includes designing jobs for safety, avoiding reliance on memory and vigilance, and simplifying and standardizing key processes (such as using checklists and protocols). Designing jobs for safety means attending to the effects of work hours, workloads, staffing ratios, appropriate training, sources of distraction and their relationship to fatigue and reduced alertness, and sleep deprivation, as well as providing appropriate training. Avoiding reliance on memory and vigilance can be accomplished in simple ways, such as instituting reminder systems and color coding, eliminating look-alike and sound-alike products, wisely using checklists and protocols, and employing more complex automated systems that may prevent many errors (though they may also introduce new sources of error). Simplification and standardization are key principles not only in delivering effective services, but also in making them safer. For example, standardization of data displays so that all are expressed in the same units, of equipment so that on-off switches are in consistent locations, of the location of supplies and equipment, of order forms, and of prescribing conventions can prevent many errors (Institute of Medicine, 2000).

Designing procedures to make errors visible can also improve safety. Although human beings will always make errors, procedures can be designed so that many errors are identified before they result in harm to patients. For example, pharmaceutical software can alert the prescriber to an incorrect dose or potential interaction with another medication (Institute of Medicine, 2000).

Designing procedures that can mitigate harm from errors is a third means of improving patient safety. Examples of this strategy are having antidotes and up-to-date information available to clinicians; having equipment that is designed to default to the least harmful mode; and ensuring that teams are trained in effective recovery from crises, such as unexpected complications during operative procedures (Institute of Medicine, 2000).

Mass Customization

Mass customization involves combining the uniqueness of customized products and services with the efficiencies of mass production. In manufacturing, this strategy has been developed as a way to give customers exactly what they want in a way that is feasible from a business standpoint—that is, quickly, at an acceptable cost, and without added complexity (Pine et al., 1995).

With reference to the three levels of predictability discussed earlier, mass customization is the design approach to Level 2 (patients with moderate levels of predictability of needs). Patients can often be grouped according to their need for a common set of services. For example, many medical conditions are defined in terms of their grade or degree of severity (e.g., cancer staging), degree of control achieved (e.g., controlled or uncontrolled hypertension), or level of risk (e.g., high- or low-risk pregnancy and the Glasgow trauma scale). With good information about the past needs and preferences of patients, it is often possible to standardize processes of care within a given stratum. It is possible to predict fairly accurately, for example, what proportion of patients will choose a variety of options, such as a group versus individual visit for management of a condition. In a non-health care example, hotels such as the Ritz Carlton keep track of their customers' preferences so they can be offered appropriate services (Gilmore and Pine, 1997).

Yet patients thus grouped are not identical, and the health system should be responsive to differences in their preferences and special needs. Mass customization involves attempting to standardize the common set of services needed by many patients while customizing or tailoring other aspects of those services to respond to individual preferences and needs. In the computer world, Internet sites can cater to “segments of one” by efficiently providing each customer with products that match his or her preferences (Leibovich, 2000). Likewise, the use of independent modules means that computer products can be assembled into different forms quickly and inexpensively (Feitzinger and Lee, 1997). Gateway is an example of a retail computer company that uses modules (such as varying amounts of memory or hard drive capacity) in mass customizing its products for the consumer. This use of modules for mass customization can be applied to the health care arena, for example to patients with congestive heart failure who need acute care. Modules for admission to a hospital or nursing home, for family education, and for rehabilitation can be drawn on and combined for individual patients. Another example is the steps in patient care, which can be thought of as a series of modules, such as (1) prescribing a medication, (2) assessing and encouraging adherence to therapy, and (3) monitoring patient outcomes. In these examples, the 80/20 approach also applies; that is, for each module, the set of options should be appropriate for 80 percent of patients.

In applying the principle of mass customization, differentiation is the last step—in industry, an example is manufacturing all products in the same way up to the addition of the product color. A health care example is having standardized instructions for patients with a given health problem, but writing in further information for those with additional health conditions.

Continuous Flow

When a patient calls to make an appointment, our philosophy is: If your doctor is here today, you will see your doctor.—Primary care practice

We have bedside registration in the emergency department. Each room receives a portable computer rolled in on a cart. Computer orders for lab and pharmacy are entered from the bedside.—Emergency department

Each morning we make rounds on all 34 intensive care patients. The discussion includes pointed, patient-oriented reports, social as well as medical needs. All such issues can be dealt with and work begun at once.—Intensive care unit

If a patient calls in with a breast lump, she is usually seen within a day or so. First she sees her primary care provider, then she is sent to us for a mammogram—usually an ultrasound as well. We can do what we think should be done right then—a biopsy and surgery if needed. Usually everything is done within 1 or 2 days.—Breast care center

Volume has dramatically increased here. We have had to change the way we work. Although most ERs have 12-hour shifts, we shortened the shifts to 9 hours. We have a system where there is “virtual on-call.” Physicians have agreed in advance that if our tracking system shows that the cycle time from the arrival of a patient to being seen by a doctor is past a specific threshold, they will stay longer, even if more help is there or on its way.—Emergency department

Continuous flow, sometimes referred to as “a batch size of one,” is an important design concept in which the system is designed to match demand so there is no aggregation of persons or units during processing. It represents the theoretical optimum for any production or service delivery system. In health care, application of this principle involves examining current assumptions about patient demand and redesigning the care process to better correspond to the characteristics of the demand curve (Murray and Tantau, 1998; Nolan et al., 1996).

If clinicians and managers assume that patient demand is insatiable, health care systems and individual practitioners must find ways to manage this demand. Management of demand generally entails using barriers, such as waiting, to dissuade some people from seeking services or reducing the need to use resources that could be used elsewhere, or both. Alternatively, if the assumption is that patient demand is steady, predictable, and reasonable, then continuous flow is a more appropriate and effective solution. Some of the most advanced examples of continuous flow have been pioneered by office practices that use “open-access” scheduling (Grandinetti, 2000; Murray, 2000; Terry, 2000). Most scheduling systems rely on distinguishing between urgent and nonurgent requests for appointments; the result is often waits of 2 weeks for a nonurgent appointment and several months for a physical examination. As a result, many patients do not keep their appointments (Bowman et al., 1996; Festinger et al., 1995). In an open-access system, office staff do not triage patients who call for an appointment on the basis of whether they believe those patients need to be seen that day. Patients can schedule an appointment and be seen the same day, if they wish, by their doctor (or nurse practitioner) if that individual is in. Continuous flow does not, however, mean that patients must be fit into a lock-step process. If they prefer to wait or schedule an appointment for the future, they are always free to do so.

To implement such a program and match demand with resources requires that a practice first deal with its backlog of future appointments. Once it has implemented an open-access process, the practice will have only one scheduling system for all patients. Practices that have implemented open access report that they are able to see as many or more patients as before; that they finish the day on time and with personnel less exhausted; and that they are providing more appropriate—effective, patient-centered, timely, and probably safer—care (Institute for Healthcare Improvement, 2000).

Under a system of continuous flow, as opposed to batch flow, practitioners dictate notes, take care of other tasks after a patient's visit, and respond to telephone messages as they occur or as patients are seen, rather than “batching” such tasks to be addressed at the end of the day. In the case of telephone messages, for example, batching often results in repeated calls by patients who are not certain their message has been received, repeated calls to patients who may be on their way home from work by the time the message is returned, delays in managing medications or in providing information about laboratory tests and instructions for self-care, and sometimes greater anxiety and suffering.

Production Planning

We reorganized into teams 2 years ago. An MD, RN, and Medical Assistant form a team. We have six or seven teams; each team sees a panel of 1200 patients. Each team sees patients for a 4 1/2-hour block of time per day. The morning starts with a 30-minute meeting to review appointments that are scheduled for the day. Then the compressed clinic day. Then time for charting each afternoon. We have practice management time that is scheduled every week. Patients are not scheduled for that time. That time is for reviewing data, collecting data. It's funny, but you can see almost the same number of patients during a compressed clinical day as during a full day. The teams are staggered throughout the day so that we can be open from 8 a.m. to 8 p.m. The number of teams is scheduled to match times when patient demand is the greatest.—Primary care practice

Production planning has been used in other industries to find the best way to allocate staff, equipment, and other resources to meet the needs of customers, as well as to reduce costs. Application of the principle depends on a detailed understanding of work processes, specifically, the identification of repetitive patterns of work.

Although the needs of patients and the work required to meet those needs will vary from day to day, all clinical practices have a natural rhythm defined by a period—for example, a week—after which the nature of the work repeats. One method of production planning involves the use of a repetitive master schedule to make the best use of resources in meeting patient needs. Creating such a schedule necessitates defining the work to be done, assembling a team suited to perform the work, understanding the time period within which the work repeats, and making work assignments based on the standard time period. If a master schedule can be built for a typical week, it can be used with minor adjustments for any week. The repetitive master schedule serves a variety of purposes. Its primary purpose is to match resources to the needs of patients, but it also provides a method for understanding complex systems and designing better production processes.

Summary

The reengineering principles described in this section—system design using the 80/20 approach, design for safety, mass customization, continuous flow, and production planning—are used by other industries, and, as indicated in the accompanying quotations, by teams across a range of health care settings that include ambulatory office practices, hospital units, emergency departments, and hospices. Such engineering principles illustrate what is meant by focusing at a system level. They enable health care teams to organize their resources effectively to better meet patient needs, and make medical practice more satisfying without driving up costs. Such deliberate crafting of systems of care results not in impersonal, one-size-fits-all care processes. Rather, it makes care safer, enables standardization where appropriate, and at the same time results in situations that meet the unique needs of each patient.

Making Effective Use of Information Technologies

Spending 1 hour each day online, I send 800–900 e-mails each month. In my former visit-based model, I would see 400–500 patients each month. Now I see 200 patients each month, in unhurried and more time intensive visits, but I communicate with over 1,000 patients each month. I feel less stressed and my patients receive better care.—Primary care practice

Chapter 7 examines in detail the potential role of information technology in improving quality. Information technology can reduce errors and harm from errors (Bates et al., 1998; Raschke et al., 1998), make up-to-date evidence and decision support systems available at the point of patient care (Berner et al., 1999; Classen, 1998; Evans et al., 1998; Hunt et al., 1998), support research (Blumenthal, 1997), help make quality measurement timely and accurate (Schneider et al., 1999), improve coordination among clinicians, and increase accountability for performance (Blumenthal, 1997; National Committee for Quality Assurance, 2000).

Increasingly, secure Internet and intranet applications are making it possible for clinicians and patients to communicate with one another more easily, for up-to-date evidence about what works to become increasingly accessible, and for clinical data to be shared in a timely fashion (Cushman and Detmer, 1998; Science Panel on Interactive Communication and Health, 1999). Some organizations have begun to implement Internet applications for their patients for such purposes as obtaining health information, communicating with one another, reading information about physicians and staff, and viewing schedules for health education classes (Kaiser Permanente Online, 2000).

Information technology can provide laboratory results and other findings, as well as tools that help clinicians apply the health literature when making diagnoses and deciding among therapeutic approaches. The validity of the information used for such decision making is obviously critical. Also important is a user interface that matches clinical workflow, cognitive style, and the time constraints of clinical practice (Kibbe and Bard, 1997b), a need that can be addressed by vendors, experts in medical informatics, and usability experts. The widespread adoption of Web-based browsers to interface with data systems has influenced medical informatics, increasing the likelihood of its acceptance and use in health care settings.

Systems that can access and combine data from many sources should be able to evolve with the uses to which they are put, the changing demands of the health care environment, and advances in technology. Such systems should be able to access all patient data wherever clinical decisions are made. They should be able to access the evidence base and decision supports, such as clinical practice guidelines. They should provide efficient means of entering orders and retrieving results. They should help practitioners coordinate activities whether they occur in the inpatient, outpatient, home, or other settings.

A handful of health care organizations have made impressive gains in automating clinical information—for example, the health systems of the Department of Veterans Affairs and Intermountain Health Care (in Salt Lake City, Utah)— but overall progress has been slow. Barriers to moving forward include the many policy (e.g., privacy concerns), technical (e.g., data standards), financial (e.g., capital requirements), and human factors (e.g., clinician acceptance) considerations discussed in Chapter 7.

Managing Clinical Knowledge and Skills

We have an intranet throughout the system that enables physicians to see the latest guidelines and recommendations about screening and to find out where each of their patients is in this care process.—Health plan-based breast care center

Our protocols for brain edema were going well. However, new literature emerged. One of the neurosurgeons recommended that we revamp the protocols to incorporate the new findings. He gathered the evidence, and the first protocol was designed by a team headed by a unit nurse. The protocol was soon standardized, and ownership was created at the physician and nurse level.— Intensive care unit

All surgeons who join the staff, regardless of seniority, start by assisting, then being assisted in 150 cases before being left on their own. If we are not completely confident they have mastered the technique, supervision is extended to another 100 cases. The secret of success is in everyone using the same technique. It decreases complications and is more cost-effective.—Small hospital specializing in two procedures

If the Respiratory Therapist notes an abnormal lab value, he or she is comfortable not just taking a blood sample and reporting it, but managing it. The technicians are caregivers. Expectations have changed. They [adjust] therapy to within physiological parameters. They are cross-trained so that they can take on nursing tasks, for example, starting IVs when needed. When fully trained and confident, they may tell an admitting doc that a patient is not ready to have a ventilator tube removed.—Intensive care unit

A key challenge for organizations, requiring a range of competencies, is translating the evidence base into practice. The competencies involved include tracking and disseminating new information, managing the clinical change that helps incorporate new information into practice, and ensuring that health care professionals have the skills they need to make use of new knowledge. All such competencies are interrelated. New information and technologies may require new skills. And new technologies, such as simulation, may enhance skills, such as those involved in performing surgical procedures or managing crises.

As described in greater detail in Chapter 6, the flood of new information that is relevant to practice can no longer be managed adequately by individual clinicians trying to keep up with the literature and attending conferences or lectures (Davis et al., 1999; Weed, 1999). One new approach to timely management of information involves including clinical librarians as a part of clinical care teams, for example, on morning rounds or on call, to note questions and search the literature for the best and most relevant information (Davidoff and Florance, 2000). Another response is to create easily accessible systematic reviews of the literature, using well-understood criteria for determining the strength of evidence and the generalizability of findings. Such systematic reviews, though important, are only the first stage, however, in disseminating the flow of new knowledge and translating it for use with individual patients. First, clinicians need evidence-based guidelines that make clear which steps are well founded and which are based on expert consensus (Institute of Medicine, 1992). These efforts may occur within practices or larger institutions, or may be developed by external entities such as specialty groups, independent organizations established for the purpose, or governmental groups. Whatever the source of such guidelines, any group that uses them needs to understand their validity and ensure that they are kept up to date.

Ensuring that new knowledge is incorporated into practice also requires a thorough understanding of how change is managed most effectively in health care, including the barriers to and facilitators of change. Knowledge about why guidelines are or are not used is accumulating, and experts now better understand the circumstances in which such strategies as education, administrative changes, incentives, penalties, feedback, and social marketing are likely to be effective (Greco and Eisenberg, 1993; Grol, 1997; Oxman et al., 1995; Solberg et al., 2000; Wensing et al., 1998) and why the translation of research findings to date has been characterized as “slow and haphazard” (Grol and Grimshaw, 1999).

One strategy for successfully managing change is to design guidelines and implementation processes so that it is easier to apply the best evidence than not to do so. This strategy begins with a systematic review of the evidence, but attends to the creation of clinical guidelines or protocols that match the logic and flow of care. Implementing this strategy also requires agreement on the part of clinicians that they will use the new guidelines and protocols, as well as the resources needed to redesign care processes (despite such resources often being scarce) so that the guidelines and protocols will become an integral and efficiently designed element of the care process.

Health care requires complex, sophisticated judgments and psychomotor skills, perhaps at a level unmatched in any other field. Other industries test judgment and psychomotor skills. In aviation, for example, simulations are used to assess competence and to help pilots improve their judgment and skills. Medicine has traditionally relied on cognitive testing of knowledge, not of judgment or skills. The field also relies on privileges granted by hospitals using various levels of rigor to assess professionals' skills, but such mechanisms do not include testing to ensure that those skills are current and have not deteriorated.

Making use of new knowledge may require that health professionals develop new skills or that their roles change. New skills might include basic technical proficiency, for example, in executing a procedure, using equipment, and interpreting data from new tests and devices. Managing new knowledge may also require the use of new psychosocial skills to elicit behavior change in patients and colleagues. Other new skills might include designing data collection efforts and managing and interpreting quality-of-care information. Finally, incorporating new knowledge requires skilled leadership to engage the participation of health professionals in collaborative teams. Leaders need to devote explicit attention to ensuring that the most appropriate individuals are trained in, maintain competence in, and are supported in their new tasks.

Developing Effective Teams

There has been a radical change since we introduced teams. You can see it even where they hang out. Before the docs were together, the nurses together, etc. But now the team hangs out with the team. At the morning meetings, you may see the medical assistants providing the leadership. The medical director calls it the “fast break”—three people on the floor and anybody can finish the play.—Primary care practice

[The doctors] are worried about managing clinical conditions. They work under pressure and stress and try to find a way to control it. They all claim that “my patients are sicker.” I reply, “Give me your sickest patients—those with congestive heart failure, the ones on coumadin, patients with diabetes, hypertension, the old, sick people, anyone who seems to require more than the average resources and time.” When they ask why I would say this, I reply, “Because I will enlist help, resources—clinical pathways, care managers.” We provide these resources to the practice and should never charge [or penalize] the doctors for this help. Doctors have not learned yet how to enhance the team with other kinds of providers—health education, behavioral medicine, physical therapy, pharmacy.—Primary care practice

Organized work groups, or multidisciplinary teams, have become a common way to organize health care, and considerable attention has been focused on their value and functioning. Such teams are found in primary care practice, in the focused care of patients with chronic conditions, in critical acute care (the intensive care unit, trauma units, operating rooms), and in geriatrics and care at the end of life. In such settings, smooth team functioning is needed because of the increasing complexity of care, the demands of new technology, and the need to coordinate multiple patient needs (Fried et al., 2000). Nonphysician team members may increase efficiency (e.g., drawing blood, giving immunizations); substitute for physicians (e.g., care for patients with simple, well-defined problems); and complement physicians (Starfield, 1992) by filling roles that physicians may not perform well or may be reluctant to undertake, such as counseling about behavior change or performing highly technical diagnostic tests. Such distributions of roles and tasks change dramatically over time. Many tasks, such as monitoring and adjusting equipment for an ill newborn after hospital discharge, have been taken over by family members and patients themselves (Hart, 1995; Lorig et al., 1993, 1999; Von Korff et al., 1997).

An IOM study of small work teams at the front lines of patient care (Donaldson and Mohr, 2000) included asking practitioners and staff who worked together on a daily basis about that experience. Respondents cited the importance of collaborative work both for clinical care and for improvement efforts. They emphasized the need to base quality improvement work within the team and to recognize the contributions that all members of the group could make, with various individuals taking leadership roles for specific improvement activities. They also described new or expanded roles and the need for coaching and training new members of the team in their work relationships.

Effective working teams must be created and maintained. Yet members of teams are typically trained in separate disciplines and educational programs, leaving them unprepared to enter practice in complex collaborative settings. They may not appreciate each other's strengths or recognize weaknesses except in crises, and they may not have been trained together to use established or new technologies (Institute of Medicine, 2000). An enormous amount of knowledge has been accumulated about team creation and management, including effective communication among team members (Fried et al., 2000). In commercial aviation, for example, emphasis is placed on crew resource management because of its importance to airline safety, and communication among flight personnel has become a special focus of proficiency checks by certified examiners (e.g., during simulated emergencies).

Considerable research has gone into identifying the characteristics of effective teams (Fried et al., 2000). These characteristics include (1) team makeup, such as having the appropriate size and composition and the ability to reduce negative effects of status differences between, for example, physicians and nurses; (2) team processes, such as communication structures, conflict management, and leadership that emphasizes excellence and conveys clear goals and expectations; (3) the nature of the team's tasks, such as matching roles and training to the level of complexity and promoting cohesiveness when work is highly interdependent; and (4) the environmental context, such as obtaining needed resources and establishing appropriate rewards. Effective teams have a culture that fosters openness, collaboration, teamwork, and learning from mistakes. Shortell et al. (1994) have demonstrated a significant relationship between better interaction among team members in intensive care units and decreased risk-adjusted length of stay. Such interaction includes the dimensions of culture, leadership, communication, coordination, problem solving, and conflict management.

Research on team interactions has also demonstrated that teams often fall short of the expectations of their clinical leaders, members, and administrative managers (Pearson and Jones, 1994). One reason is that medical education emphasizes hierarchy and the importance of assuming individual responsibility for decision making. An emphasis on personal accountability comes at the price of losing the contribution of others who may bring added insight and relevant information, whatever their formal credentials. Acculturation to medical roles makes it difficult for members of a team to point out or admit to safety problems and thereby prevent harm. Indeed, challenges to those in positions of power and authority by nurses, physicians in training, and others is notoriously difficult and discouraged (Helmreich, 2000; Institute of Medicine, 2000). Avoiding overt hostility over a slip or lapse and acknowledging shared knowledge and proficiency when recovering from unexpected patient events (Helmreich, 2000) are examples of how strong collaborative working relationships can improve patient safety.

In health care environments characterized by uncertainty, instability, and variability (such as operating rooms and intensive care units), high levels of stress are common (Mark and Hagenmueller, 1994; Perrow, 1967). Other environments do not have the level of instability and uncertainty associated with critical care units and operating suites, yet the complexity of patients' needs still necessitates highly effective coordination of resources across a spectrum of settings, disciplines, and the community. An example is the care of frail elderly patients, in which the ability to coordinate care and assemble effectively functioning health care teams is paramount, and flexibility in role functioning may be key.

In Chapter 3, new rule 10 emphasizes the importance of collaboration for effective team functioning. What is sometimes thought to be collaboration, however, may in fact be uncoordinated or sequential action rather than collaborative work. That is, the work of each individual may be efficient from the perspective of his or her own tasks, but overall the efforts are suboptimal and do not serve the needs of patients. An example of suboptimization may occur when an elderly woman breaks her hip and comes to the emergency department. She may spend several hours receiving x-rays and being stabilized and will certainly need to be admitted. At the end of this time, someone may call to notify the nursing staff that the patient is being admitted, and several hours more may elapse while admission orders are written and the patient's room is made available. When emergency department and floor staff collaborate, notification is given immediately after the patient arrives in the emergency department so that the admission process can begin, and the patient can go from the emergency department directly to her hospital room, where she will be much more comfortable. In such cases and in many others, running parallel processes reduces delays and improves outcomes (Nugent et al., 1999).

Coordinating Care Across Patient Conditions, Services, and Settings Over Time

That is fundamental to what is important to me—that the focus be on the individual—a complex person—and you try to do the best you can for them. It seems odd to say, but that is what is fun. We did focus groups with families and learned key things that are important: (1) the organization and delivery of care, (2) shared medical decision making, (3) treating each person as an individual, and (4) attending to those who care for and love the dying person. The building blocks to accomplish this are information and education of the patient and family, coordination, and continuity.—Hospice

Another key challenge for organizations is coordination (or clinical integration) of work across services that are complementary, such as emergency response units, emergency departments, and operating suites, or across primary care practices, specialty practices, and laboratories to which patients are referred. Clinical integration can be defined as “the extent to which patient care services are coordinated across people, functions, activities, and sites over time so as to maximize the value of services delivered to patients” (Shortell et al., 2000a). In particular, coordination encompasses a set of practitioner behaviors and information systems intended to bring together health services, patient needs, and streams of information to facilitate the aims of care set forth in Chapter 2. For example, coordination may involve ensuring that treating physicians are informed about diagnostic results, therapies attempted during an earlier hospital admission, and the effectiveness of those efforts. Coordination may involve nurse case managers transmitting information to both primary and specialty care practitioners about a patient's unmet needs. Such coordination may be facilitated as well by procedures for engaging community resources (such as social and public health services) and other sites of care (such as hospice or home care) when and as appropriate.

Coordination of care across clinicians and settings has been shown to result in greater efficiency and better clinical outcomes (Aiken et al., 1997; Gittell et al., 2000; Knaus et al., 1986; Shortell et al., 1994, 2000a, 2000b). Optimizing care for a patient with a complex chronic condition is challenging enough, but optimizing care for patients with several chronic conditions and acute episodes, as well as meeting health maintenance needs, represents an extraordinary challenge for today's health care systems (MacLean et al., 2000; Shortell et al., 2000a). The challenges arise at many organizational levels and across the full range of tasks, including the design, dissemination, implementation, and modification of care processes and the payment for these tasks. What is important to patients and their families is that effective systems for transferring patient-related information be in place so that the information is accurate and available when needed. Patients and their families need to know who is responsible for decisions and can answer questions, and to be assured that gaps in responsibility will not occur.

Some problems—such as substance abuse, AIDS, and domestic violence— are so interrelated that they appear to require a comprehensive rather than problem-by-problem approach (Shortell et al., 2000a). Other problems require assembling and making the best use of an array of resources, such as the numerous federal programs that might be involved in obtaining and paying for a wheelchair for a child with special needs. In any case, if care is to move beyond single solutions crafted by individual clinicians (as in the Stage 1 delivery of care described earlier in this chapter), it will require an accurate understanding of patient needs so that standard processes can be provided and individual solutions crafted as appropriate. Newly developed infrastructures, information technologies, and well-thought-out and -implemented modes of communication can reduce the need to craft laborious, case-by-case strategies for coordinating patient care. A variety of other mechanisms can improve coordination, such as involving a combination of individuals (e.g., clinicians, members of multidisciplinary teams, care managers), along with patients and their families.

Some patients and their families become so expert in their condition that they choose to coordinate care for themselves or a family member. Those who do so are likely to need new skills in accessing information and new technologies for structuring and conveying information to others who are involved in their care. For example, patients can contribute to flow sheets, respond to questions about changes in health status, or upload data from micromonitoring devices worn on the body or from home monitoring devices. Not all patients or their families (or perhaps even most) will choose or be able to become central actors in coordinating their own care, however. In such cases, appropriate mechanisms within the delivery system must be available to meet this responsibility.

One means of improving coordination is based on what are sometimes called clinical pathways. These blueprints for care set forth a set of services needed for patients with a given health problem and the sequence in which they should take place. For some conditions, a set of clearly identified processes should occur. In complex adaptive systems such as health care, however, few patient care processes are linear (such as the transition from hospital to nursing home). Rather, most organizational processes are reciprocal and interdependent (Thompson, 1967), and coordination requires the design of procedures that are responsive both to variations among individual patients and to unexpected occurrences.

Incorporating Performance and Outcome Measurements for Improvement and Accountability

We have a Clinical Roadmap team for breast cancer screening. The team has formulated four criteria for success that include process and outcome measures. They are (1) the proportion of women in our population who have received care in the last 2 years; (2) the number of women who came to the screening program when invited; (3) the number of women in the program who develop a late stage disease; and (4) survey responses during the time of enrollment in the program. These criteria give us specific as well as broad measures of success.—Breast care center

We have a clinical “instrument panel.” We measure cycle time, patient satisfaction, phone calls (incoming and outgoing), proportion reaching treatment goals for hypertension, operating costs per visit, proportion of patients seeing their provider of choice, available appointments, team morale, practice size, and proportion of pap smears in eligible women.—Primary care practice

The main outcome measure is risk adjusted mortality. We compare ourselves quarterly to similar institutions for observed versus predicted mortality on one axis and resource consumption on the other. Using 50 percent random sampling, we track mortality, admission and discharge rates, length of stay, number of patients readmitted to the ICU, and reintubation rates. This helps us know if changes that affect efficiency are affecting quality of care. Although our admissions are up, length of stay is down significantly, and our reintubation rate is very low.—Critical care unit

Although we generally think of individuals as learning and enhancing their capabilities, it is also possible to think of an organization as learning—increasing its competence and responsiveness and improving its work (Davies and Nutley, 2000). The committee believes moving toward the health system of the 21st century will require that health care organizations successfully address the challenge of becoming learning organizations. A decade ago, Senge and others (Argyris and Schön, 1978; Senge, 1990) described such organizations as those that can learn quickly and accurately about their environment and translate this learning to the work they do. This idea has been incorporated in the work of many companies, most outside of health care—such as 3M, Boeing, the Cadillac Division of General Motors, Fedex, Motorola, and Xerox—whose drive to reduce defects and improve quality and customer service has been recognized by the Malcolm Baldrige National Quality Award (National Institute of Standards and Technology, 2000b).

In Senge's terminology, “single-loop” learning results in incremental improvements in existing practice. In health care it might involve efforts to decrease waiting time for follow-up appointments for patients who have an abnormal laboratory test result. Another feature of learning organizations is their reexamination of mental models or assumptions on which they base their work, giving rise to “double-loop” learning. An example of double-loop learning is rethinking and reorganizing all ancillary and specialty medical services for women in a breast care center to eliminate any waiting between reporting of abnormal mammographic findings, definitive diagnosis, and therapy.

A critical feature of learning organizations is the ability to be aware of their own “behavior.” In organizational terms, this means having data that allow the organization to track what has happened and what needs to happen—in other words, to assess its performance and use that information to improve. The committee is convinced that a major tool for accomplishing this critical function is the investment in and use of an effective information infrastructure to develop a balanced set of measures on, for example, clinical and financial performance, patient health outcomes, and satisfaction with care (Nelson et al., 1996). It is important that such measures be balanced—that they include a variety of measures so that when changes are made in processes, such as to increase efficiency, other outcomes, such as patient health, are not adversely affected.

Clinical practices that participated in the IOM study of exemplary practices (Donaldson and Mohr, 2000) described how routine measurement has become part of their production process. Ideally, such measures can be aggregated for external reporting, whether to support contract discussions or to help patients make choices about where and from whom to seek care. Building measurement into the production process can counter the perception on the part of many health care leaders that reporting is a burden. Such a perception results when organizations must respond to numerous demands from external groups for quality measures, especially if those measures lack specificity or relevance to the clinical teams that must generate them.

Measures need not involve expensive, large-scale, long-term evaluation projects to be useful. New methods that use sampling and small-scale rapid-cycle testing, modification, and retesting are proving useful in dynamic settings such as patient care units (Berwick, 1996; Langley et al., 1996). As other world-class businesses have learned, including American industry giants (Walton and Deming, 1986), attention to improving quality includes continuous monitoring, often based on small samples of events, that can provide organizations with timely data at the front lines to manage the processes of concern (James, 1989; Rainey et al., 1998; Scholtes, 1988). In the IOM study of exemplary practices, several health care teams described their use of such methods to manage their care processes (Donaldson and Mohr, 2000).

It's an incredible relief to try small changes on a small scale. It's so simple it's brilliant. We had been managing indigent diabetic patients for years and didn't think we could do any better. The providers believed that these people are so hard. But the patients responded to the changes we made. You have to craft something that is doable. You have to look for the simplicity in complex things.—Diabetic management group for underserved minorities

We have embraced the concept of “real-time tracking.” We have developed a “radar screen” that has 8 simultaneous processes continuously monitored. We get information on the census in the ER, the status of the patients, the x-ray cycle, etc. We know where in the process not only the patient is, but where the system is. Each process measured is summarized on the screen by graphs. All we have to do to obtain data is touch the screen. The graphs are equipped with goal lines that are based on customer satisfaction, for example waiting time.— Community based emergency department

The key word to describe a micro-system is homeostasis. A micro-system is always changing and adapting, just like the human body. We have identified the “pathophysiology” of a micro-system. It is powerful, yet very predictable. Think about two downstream processes, x-ray cycle time and getting patients to the floor. If the downstream [processes] get out of control, there are predictable changes in the system. Occupancy in the ER goes up, the number of new patients seen in the ER goes down, the number of free beds in the ER goes down, and the cycle time between a patient's arrival to a bed goes up. Eventually, every measurement goes up. When we obtain three consecutive 15-minute intervals going the wrong way, we realize that something needs to be done.— Community based Emergency Department.

LEADERSHIP FOR MANAGING CHANGE

The role of leaders is to define and communicate the purpose of the organization clearly and establish the work of practice teams as being of highest strategic importance. Leaders must be responsible for creating and articulating the organization's vision and goals, listening to the needs and aspirations of those working on the front lines, providing direction, creating incentives for change, aligning and integrating improvement efforts, and creating a supportive environment and a culture of continuous improvement that encourage and enable success.

Learning organizations need leadership at many levels that can provide clear strategic and sustained direction and a coherent set of values and incentives to guide group and individual actions. The first criterion of performance excellence for health care organizations listed by the Baldrige National Quality Program is the provision of “a patient focus, clear and visible values, and high expectations” by the organization's senior leaders (National Institute of Standards and Technology, 2000a). Indeed, strong management leadership in hospitals is positively associated with greater clinical involvement in quality improvement (Weiner et al., 1996, 1997).

Leaders of health care organizations may need to provide an environment for innovation that allows for new and more flexible roles and responsibilities for health care workers; and supports the accomplishments of innovators despite regulatory, legal, financial, and sometimes interprofessional conflict (Donaldson and Mohr, 2000). Leaders need to provide such an environment because the learning, adaptation, and incorporation of best practices needed to effect engineering changes requires energy that is scarce in a demanding and rapidly changing environment.

At the level of front-line teams, leaders should encourage the members of the team to engage in deliberate inquiry—using their own observations and ideas to improve safety and quality. The individual who serves as leader may not be constant over time or across innovative efforts, or be associated with a particular discipline, such as medicine. What is important is for the leader to understand how units relate to each other—a form of systems thinking—and to facilitate the transfer of learning across units and practices.

Leaders of health care organizations must fill a number of specific roles. First, they must identify and prioritize community health needs and support the organization's ability to meet these needs. Addressing community needs might involve collaboration with other community or health care organizations and the creation of new services. Examples include providing CPR training for a major employer and identifying and alerting the community to patterns of injury, such as the number of children with head injuries from bicycle accidents, or a newly appearing occupational illness. Other examples include addressing the more complex needs for coordinated local social and health services presented by low-income ill elderly individuals or the need for more accessible substance abuse treatment facilities. Leaders of organizations can support accountability to individual patients while also assuming responsibility for accountability to public bodies and the community at large for the populations they serve.

Second, leaders can help obtain resources and respond to changes in the health care environment, which have been rapid and unrelenting. Leaders must ensure that their organization has the ability to change. Yet many leaders now view their role as shielding and protecting the organization from environmental pressures that may require them to change. Leadership should support innovation and provide a forum so that individuals can continuously learn from each other. Organizations must invest in innovation and redesign.

Third, and perhaps the most difficult leadership role, is to optimize the performance of teams that provide various services in pursuit of a shared set of aims. In any complex organization, there is danger in supporting some clinical services (perhaps those that are most profitable) to the detriment of the whole system. Leaders must strive to align the strategic priorities of their organization, its resources (financial and human), and support mechanisms (e.g., information systems). Balancing these elements can be extremely difficult and requires leaders to have a performance measurement capability that includes measures of safety, effectiveness, patient-centeredness, timeliness, efficiency, and equity.

Fourth, leaders can support reward and recognition systems that are consistent with and supportive of the new rules set forth in Chapter 3 and that facilitate coordination of work across sets of services as necessary. Organizations should support an environment in which incentives to provide effective care are not distorted before they reach caregivers. An example of distortion is a payment system based solely on the numbers of home care visits made by a visiting nurse per day. This sort of productivity measure prevents nurses from focusing on patient needs. A system based on effectively caring for a given number of patients recognizes that a predictable mix of needs will occur over a period of time, and can encourage small teams to organize themselves to meet those needs. Such decision making can be very difficult, especially in the current economic environment and payment system (see Chapter 8).

Fifth, leaders need to invest in their workforce to help them achieve their full potential, both individually and as a team, in serving their patients. The resulting interpersonal and technical competence can produce the synergies and improved outcomes that emerge from collaborative work.

Although the leadership roles described are not novel, the orientation toward facilitating the work of health care teams represents a fundamental shift in perspective. The new rules set forth in Chapter 3 and the engineering principles described in this chapter will require strong and visible leadership with corresponding reward structures. All organizations must overcome their inherent resistance to change. It is role of leaders to surmount these barriers by visibly promoting the need for improvement, becoming role models for the required new behaviors, providing the necessary resources, and aligning recognition and reward systems in support of improvement goals. Leadership's role in promoting innovation, gathering feedback, and recognizing progress is essential to successful and sustained improvement.

Finally, leaders must recognize the interdependence of changes at all levels of the organization—individual, group or team, organizational, and interorganizational—in addressing the six challenges discussed in this chapter. For example, providing additional training in error correction or technical skill development to individuals without recognizing that they work as part of a team will have little impact. Similarly, working to develop more effective teams without recognizing that they are part of a complex organization with frequently misaligned incentives will have little effect on improving quality. Likewise, trying to redesign organizational structures and incentives and revise organizational cultures without taking into account the specific needs of teams and individuals is likely to be an exercise in frustration. And attempting to make changes at any of these levels without recognizing the larger interorganizational networks that include other providers, payers, and legal and regulatory bodies (as discussed in subsequent chapters) is likely to result in the waste of well-intended plans and energy.

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Copyright 2001 by the National Academy of Sciences. All rights reserved.
Bookshelf ID: NBK222276

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